A Computational Platform for Automatic Signal Processing for Bender Element Sensors

Author:

Moldovan Ionuţ Dragoş12ORCID,Almukashfi Abdalla3ORCID,Gomes Correia António3ORCID

Affiliation:

1. Faculty of Engineering, Lusófona University, 1700-097 Lisbon, Portugal

2. CERIS, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal

3. Instituto para a Sustentabilidade e Inovação em Estruturas de Engenharia (ISISE), Universidade do Minho, 4800-058 Guimarães, Portugal

Abstract

The small strain shear modulus is an important characteristic of geomaterials that can be measured experimentally using piezoelectric sensors (bender elements). However, most conventional signal interpretation techniques are based on the visual observation of the output signal and therefore inherently subjective. Objective techniques also exist, like the cross-correlation of the input and output signals, but they lack physical insight, as they rely on the (incorrect) assumption that input and output signals are similar. This paper presents GeoHyTE, the first objective and physically consistent toolbox for the automatic processing of the output signal of bender element sensors. GeoHyTE updates a finite element model of the experiment, iteratively searching for the small strain shear modulus that maximises the correlation between the experimental and numerical output signals. The method is objective, as the results do not depend on the experience of the user, and physically consistent, as the wave propagation process is modelled in full and signals of the same nature (output) are correlated. Moreover, GeoHyTE is nearly insensitive to grossly erroneous input by the user, both in terms of the starting point of the iterative maximisation process and refinement of the finite element model. The results obtained with GeoHyTE are validated against benchmark measurements reported in the literature and experimental data obtained by the authors. A detailed statistical analysis of the results obtained with GeoHyTE and conventional interpretation techniques is also presented.

Funder

FCT/MCTES through national funds (PIDDAC) under the R&D Units Institute for Sustainability and Innovation in Structural Engineering

Civil Engineering Research and Innovation for Sustainability

Associate Laboratory Advanced Production and Intelligent Systems ARISE

Fundação para a Ciência e a Tecnologia

Publisher

MDPI AG

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